Related papers: Automatic detection of CMEs using synthetically-tr…
Recently, there has been a high demand for accelerating and improving the detection of automatic cadastral mapping. As this problem is in its starting point, there are many methods of computer vision and deep learning that have not been…
Coronal Mass Ejections (CMEs) are energetic storms in the Sun that result in the ejection of large-scale magnetic clouds (MCs) in interplanetary space that contain enhanced magnetic fields with coherently changing field direction. The…
In this work we predict vehicle speed and steering angle given camera image frames. Our key contribution is using an external pre-trained neural network for segmentation. We augment the raw images with their segmentation masks and mirror…
Coronal mass ejections (CMEs) are violent ejections of magnetized plasma from the Sun, which can trigger geomagnetic storms, endanger satellite operations and destroy electrical infrastructures on the Earth. After systematically searching…
Coronal mass ejections (CMEs) are the eruptions of magnetised plasma from the Sun and are considered the main driver of adverse space weather events. Hence, undrstanding its formation process, particularly the magnetic topology, is critical…
We investigate how a weak coronal mass ejection (CME) launched on 2016 October 8 without obvious signatures in the low corona produced a relatively intense geomagnetic storm. Remote sensing observations from SDO, STEREO and SOHO and in situ…
Automated semantic image segmentation is an essential step in quantitative image analysis and disease diagnosis. This study investigates the performance of a deep learning-based model for lung segmentation from CT images for normal and…
Context-based detection methods such as DetectGPT achieve strong generalization in identifying AI-generated text by evaluating content compatibility with a model's learned distribution. In contrast, existing image detectors rely on…
In this paper we present a new method for cystoid macular edema (CME) segmentation in retinal Optical Coherence Tomography (OCT) images, using a fully convolutional neural network (FCN) and a fully connected conditional random fields (dense…
Measuring the physical parameters of Coronal Mass Ejections (CMEs), particularly their entrained magnetic field, is crucial for understanding their physics and for assessing their geo-effectiveness. At the moment, only remote sensing…
The segmentation of diseases is a popular topic explored by researchers in the field of machine learning. Brain tumors are extremely dangerous and require the utmost precision to segment for a successful surgery. Patients with tumors…
Solar coronal mass ejections (CMEs) are the most significant drivers of adverse space weather at Earth, but the physics governing their propagation through the heliosphere is not well understood. While stereoscopic imaging of CMEs with the…
The paper presents the results from a multi-year effort to develop and validate image processing methods for selecting the best physical models based on solar image observations. The approach consists of selecting the physical models based…
Context. Stellar coronal mass ejections (CMEs) are the primary driver of the exoplanetary space weather and they could affect the habitability of exoplanets. However, detections of possible stellar CME signatures are extremely rare. Aims.…
Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue…
A fundamental property of coronal mass ejections (CMEs) is their radial expansion, which determines the increase in the CME radial size and the decrease in the CME magnetic field strength as the CME propagates. CME radial expansion can be…
The present study proposes a new approach to automated screening of Clinically Significant Macular Edema (CSME) and addresses two major challenges associated with such screenings, i.e., exudate segmentation and imbalanced datasets. The…
Semantic segmentation using convolutional neural networks (CNNs) is the state-of-the-art for many medical image segmentation tasks including myocardial segmentation in cardiac MR images. However, the predicted segmentation maps obtained…
Stellar flares and coronal mass ejections (CMEs) can strip planetary atmospheres, reducing the potential habitability of terrestrial planets. While flares have been observed for decades, stellar CMEs remain elusive. Extreme ultraviolet…
Some of the major challenges faced in understanding the early evolution of Coronal Mass Ejections (CMEs) are due to limited observations in the inner corona ($<\,3$ R$_{\odot}$) and the plane of sky measurements. In this work, we have thus…